前言
無損壓縮領域最爲常見的算法當屬霍夫曼壓縮算法了。其主要思想是放棄文本文件的傳統保存方式,不再使用八位二進制數表示每一個字符,而是用較少的比特表示出現頻率較高的字符,用較多的比特表示出現頻率較低的字符。
在圖像數據壓縮時,遊程編碼和霍夫曼編碼也是十分常用的。
變長前綴碼
和每個字符所相關的編碼都是一個比特字符串,就好像有一個以字符爲鍵、比特字符串爲值得符號表一樣。我們可以試着將最短得比特字符賦予最常用的字符,將A編碼爲0、B編碼爲1、R編碼爲00。這樣一來問題就出現了,A的編碼是0,R的編碼是00,那麼當0出現的時候,我們應該認爲其是A還是R的前綴呢?如果你不想引入分隔符的話,這個時候就需要引入變長前綴碼。
在變長前綴碼中,所有字符編碼都不會成爲其它字符編碼的前綴,那麼如此就不需要分隔符了。
前綴碼的實現
前綴碼的實現採用了單詞查找樹。
自制Huffman壓縮和解壓工具
網址如下,點擊此處跳轉
https://download.csdn.net/download/m0_37772174/11965071
自制工具是exe文件
壓縮命令 :SZip A inputfilename outputfilename
解壓縮命令:SZip X inputfilename outputfilename
Python 代碼
'''
@file huffman.py
'''
import heapq
import os
from functools import total_ordering
@total_ordering
class HeapNode:
def __init__(self, char, freq):
self.char = char
self.freq = freq
self.left = None
self.right = None
# defining comparators less_than and equals
def __lt__(self, other):
return self.freq < other.freq
def __eq__(self, other):
if(other == None):
return False
if(not isinstance(other, HeapNode)):
return False
return self.freq == other.freq
class HuffmanCoding:
def __init__(self, path):
self.path = path
self.heap = []
self.codes = {}
self.reverse_mapping = {}
# functions for compression:
def make_frequency_dict(self, text):
frequency = {}
for character in text:
if not character in frequency:
frequency[character] = 0
frequency[character] += 1
return frequency
def make_heap(self, frequency):
for key in frequency:
node = HeapNode(key, frequency[key])
heapq.heappush(self.heap, node)
def merge_nodes(self):
while(len(self.heap)>1):
node1 = heapq.heappop(self.heap)
node2 = heapq.heappop(self.heap)
merged = HeapNode(None, node1.freq + node2.freq)
merged.left = node1
merged.right = node2
heapq.heappush(self.heap, merged)
def make_codes_helper(self, root, current_code):
if(root == None):
return
if(root.char != None):
self.codes[root.char] = current_code
self.reverse_mapping[current_code] = root.char
return
self.make_codes_helper(root.left, current_code + "0")
self.make_codes_helper(root.right, current_code + "1")
def make_codes(self):
root = heapq.heappop(self.heap)
current_code = ""
self.make_codes_helper(root, current_code)
def get_encoded_text(self, text):
encoded_text = ""
for character in text:
encoded_text += self.codes[character]
return encoded_text
def pad_encoded_text(self, encoded_text):
extra_padding = 8 - len(encoded_text) % 8
for i in range(extra_padding):
encoded_text += "0"
padded_info = "{0:08b}".format(extra_padding)
encoded_text = padded_info + encoded_text
return encoded_text
def get_byte_array(self, padded_encoded_text):
if(len(padded_encoded_text) % 8 != 0):
print("Encoded text not padded properly")
exit(0)
b = bytearray()
for i in range(0, len(padded_encoded_text), 8):
byte = padded_encoded_text[i:i+8]
b.append(int(byte, 2))
return b
def compress(self):
filename, file_extension = os.path.splitext(self.path)
output_path = filename + ".bin"
with open(self.path, 'r+') as file, open(output_path, 'wb') as output:
text = file.read()
text = text.rstrip()
frequency = self.make_frequency_dict(text)
self.make_heap(frequency)
self.merge_nodes()
self.make_codes()
encoded_text = self.get_encoded_text(text)
padded_encoded_text = self.pad_encoded_text(encoded_text)
b = self.get_byte_array(padded_encoded_text)
output.write(bytes(b))
print("Compressed")
return output_path
""" functions for decompression: """
def remove_padding(self, padded_encoded_text):
padded_info = padded_encoded_text[:8]
extra_padding = int(padded_info, 2)
padded_encoded_text = padded_encoded_text[8:]
encoded_text = padded_encoded_text[:-1*extra_padding]
return encoded_text
def decode_text(self, encoded_text):
current_code = ""
decoded_text = ""
for bit in encoded_text:
current_code += bit
if(current_code in self.reverse_mapping):
character = self.reverse_mapping[current_code]
decoded_text += character
current_code = ""
return decoded_text
def decompress(self, input_path):
filename, file_extension = os.path.splitext(self.path)
output_path = filename + "_decompressed" + ".txt"
with open(input_path, 'rb') as file, open(output_path, 'w') as output:
bit_string = ""
byte = file.read(1)
while(len(byte) > 0):
byte = ord(byte)
bits = bin(byte)[2:].rjust(8, '0')
bit_string += bits
byte = file.read(1)
encoded_text = self.remove_padding(bit_string)
decompressed_text = self.decode_text(encoded_text)
output.write(decompressed_text)
print("Decompressed")
return output_path
#@file main.py
from huffman import HuffmanCoding
path = "test.txt"
h = HuffmanCoding(path)
output_path = h.compress()
print("Compressed file path: " + output_path)
decom_path = h.decompress(output_path)
print("Decompressed file path: " + decom_path)